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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Hoogakker, Babette A A; Chapman, Mark R; McCave, I Nick; Hillaire-Marcel, Claude; +3 Authors

    High resolution flow speed reconstructions of two core sites located on Gardar Drift in the northeast Atlantic Basin and Orphan Knoll in the northwest Atlantic Basin reveal a long-term decrease in flow speed of Northeast Atlantic Deep Water (NEADW) after 6,500 years. Benthic foraminiferal oxygen isotopes of sites currently bathed in NEADW show a 0.2per mil depletion after 6,500 years, shortly after the start of the development of a carbon isotope gradient between NEADW and Norwegian Sea Deep Water. We consider these changes in near-bottom flow vigor and benthic foraminiferal isotope records to mark a significant reorganization of the Holocene deep ocean circulation, and attribute the changes to a weakening of NEADW flow during the mid to late Holocene that allowed the shoaling of Lower Deep Water and deeper eastward advection of Labrador Sea Water into the northeast Atlantic Basin. MD99-2251 originally published in Ellsion et al., (2006). Conversion to calendar years before present (cal. yrs BP) with CALIB 501 (Stuiver et al., 1993) using marine04 as calibration data set. Mean ages are the arithmetic means of the age ranges given by the program. Supplement to: Hoogakker, Babette A A; Chapman, Mark R; McCave, I Nick; Hillaire-Marcel, Claude; Ellison, Christopher RW; Hall, Ian R; Telford, Richard J (2011): Dynamics of North Atlantic Deep Water masses during the Holocene. Paleoceanography, 26(4), PA4214

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEAarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2011
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA - Data Publisher for Earth and Environmental Science
    Other dataset type . 2011
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEAarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PANGAEA
      Dataset . 2011
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PANGAEA - Data Publisher for Earth and Environmental Science
      Other dataset type . 2011
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Mendoza, Irene; Peres, Carlos Augusto; Morellato, Leonor Patricia C;

    Changes in the life cycle of organisms (i.e. phenology) are one of the most widely used early-warning indicators of climate change, yet this remains poorly understood throughout the tropics. We exhaustively reviewed any published and unpublished study on fruiting phenology carried out at the community level in the American tropics and subtropics (latitudinal range: 26°N?26°S) to (1) provide a comprehensive overview of the current status of fruiting phenology research throughout the Neotropics; (2) unravel the climatic factors that have been widely reported as drivers of fruiting phenology; and (3) provide a preliminary assessment of the potential phenological responses of plants under future climatic scenarios. Despite the large number of phenological datasets uncovered (218), our review shows that their geographic distribution is very uneven and insufficient for the large surface of the Neotropics (~ 1 dataset per ~ 78,000 km2). Phenological research is concentrated in few areas with many studies (state of São Paulo, Brazil, and Costa Rica), whereas vast regions elsewhere are entirely unstudied. Sampling effort in fruiting phenology studies was generally low: the majority of datasets targeted fewer than 100 plant species (71%), lasted 2 years or less (72%), and only 10.4% monitored > 15 individuals per species. We uncovered only 10 sites with ten or more years of phenological monitoring. The ratio of numbers of species sampled to overall estimates of plant species richness was wholly insufficient for highly diverse vegetation types such as tropical rainforests, seasonal forest and cerrado, and only slightly more robust for less diverse vegetation types, such as deserts, arid shrublands and open grassy savannas. Most plausible drivers of phenology extracted from these datasets were environmental (78.5%), whereas biotic drivers were rare (6%). Among climatic factors, rainfall was explicitly included in 73.4% of cases, followed by air temperature (19.3%). Other environmental cues such as water level (6%), solar radiation or photoperiod (3.2%), and ENSO events (1.4%) were rarely addressed. In addition, drivers were analyzed statistically in only 38% of datasets and techniques were basically correlative, with only 4.8% of studies including any consideration of the inherently autocorrelated character of phenological time series. Fruiting peaks were significantly more often reported during the rainy season both in rainforests and cerrado woodlands, which is at odds with the relatively aseasonal character of the former vegetation type. Given that climatic models predict harsh future conditions for the tropics, we urgently need to determine the magnitude of changes in plant reproductive phenology and distinguish those from cyclical oscillations. Long-term monitoring and herbarium data are therefore key for detecting these trends. Our review shows that the unevenness in geographic distribution of studies, and diversity of sampling methods, vegetation types, and research motivation hinder the emergence of clear general phenological patterns and drivers for the Neotropics. We therefore call for prioritizing research in unexplored areas, and improving the quantitative component and statistical design of reproductive phenology studies to enhance our predictions of climate change impacts on tropical plants and animals. This file contains collated datasets including phenological information of fruiting in the Neotropics. They are part of an invited review submitted to Global and Planetary Change. Each dataset collated in our review was distinguished with a different ID. Complete reference, geographical coordinates (latitude and longitude), information about sampling procedures, sampling effort in terms of the number of individuals, species or seed traps used, study length monitoring, vegetation type and life herb forms are included. Supplement to: Mendoza, Irene; Peres, Carlos Augusto; Morellato, Leonor Patricia C (2016): Continental-scale patterns and climatic drivers of fruiting phenology: A quantitative Neotropical review. Global and Planetary Change

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEAarrow_drop_down
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    PANGAEA
    Dataset . 2016
    Data sources: B2FIND
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    PANGAEA - Data Publisher for Earth and Environmental Science
    Other dataset type . 2016
    License: CC BY
    Data sources: Datacite
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      PANGAEA
      Dataset . 2016
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PANGAEA - Data Publisher for Earth and Environmental Science
      Other dataset type . 2016
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Tzedakis, Polychronis C; Margari, Vasiliki; Skinner, Luke C; Menviel, Laurie; +7 Authors

    Benthic foraminifera oxygen isotopes: The benthic isotope record was generated by the late N.J. Shackleton. Measurements were carried out in the Godwin Laboratory for Palaeoclimate Research (University of Cambridge), using a VG PRISM mass spectrometer. Where possible two or three separate analyses of different benthic species were made in each sample; a correction factor was applied according to the species and the average of all the corrected values at each level is shown in the figures. The following species were analysed, and adjusted as indicated: Cibicidoides sp.: +0.51; Uvigerina peregrina and similar specimens: 0.0; Globobulimina affinis: -0.4; Cibicidoides wuellerstorfi, +0.64; Globocassidulina sp.: -0.1; Hoeglundina elegans: -0.7. These adjustments are optimized for this particular core in accordance with the long-standing convention by which Uvigerina peregrina is assumed to deposit oxygen in isotopic equilibrium. Results are reported with reference to the international standard VPDB and the precision is better than ±0.08‰ for d18O. Age model: The age model was developed by aligning the abrupt transitions of d18O record of G. bulloides in core MD01-2444 to warming and cooling events in the NGRIP d18Oice record, presented on: (i) the GICC05 timescale [Svensson, A. et al. A 60,000 year Greenland stratigraphic ice core chronology. Clim. Past 4, 47–57 (2008)]; and (ii) the WD2014: modified timescale, whereby NGRIP GICC05 ice ages 31.2–67.2 ka are multiplied by 1.0063. [Buizert, C. et al. The WAIS Divide deep ice core WD2014 chronology – Part 1: Methane synchronization (68–31 ka BP) and the gas age–ice age difference. Clim. Past 11, 153-173 (2015)].

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2020
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2020
      Data sources: B2FIND
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    Authors: Tzedakis, Polychronis C; Margari, Vasiliki; Skinner, Luke C; Menviel, Laurie; +7 Authors

    Planktonic foraminifera (G. bulloides) oxygen isotopes: Measurements of foraminiferal stable isotopes were carried out in the Godwin Laboratory for Palaeoclimate Research (University of Cambridge), using a VG SIRA mass spectrometer. Analyses were made on samples consisting of 30 specimens of G. bulloides in the 300-355 mm size fraction, picked by M.J. Mleneck-Vautravers. Results are reported with reference to the international standard VPDB and the precision is better than ±0.08‰ for d18O. Age model: The age model was developed by aligning the abrupt transitions of d18O record of G. bulloides in core MD01-2444 to warming and cooling events in the NGRIP d18Oice record, presented on: (i) the GICC05 timescale [Svensson, A. et al. A 60,000 year Greenland stratigraphic ice core chronology. Clim. Past 4, 47–57 (2008)]; and (ii) the WD2014: modified timescale, whereby NGRIP GICC05 ice ages 31.2–67.2 ka are multiplied by 1.0063. [Buizert, C. et al. The WAIS Divide deep ice core WD2014 chronology – Part 1: Methane synchronization (68–31 ka BP) and the gas age–ice age difference. Clim. Past 11, 153-173 (2015)].

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEAarrow_drop_down
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    PANGAEA
    Dataset . 2020
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      PANGAEA
      Dataset . 2020
      Data sources: B2FIND
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    Authors: Verbruggen, Erik; El Mouden, Claire; Jansa, Jan; Akkermans, Geert; +3 Authors

    Explaining mutualistic cooperation between species remains a major challenge for evolutionary biology. Why cooperate if defection potentially reaps greater benefits? It is commonly assumed that spatial structure (limited dispersal) aligns the interests of mutualistic partners. But does spatial structure consistently promote cooperation? Here, we formally model the role of spatial structure in maintaining mutualism. We show theoretically that spatial structure can actually disfavour cooperation by limiting the suite of potential partners. The effect of spatial structuring depends on the scale (fine or coarse level) at which hosts reward their partners. We then test our predictions by using novel molecular methods to track the abundance of competing, closely-related, cooperative and less-cooperative arbuscular mycorrhizal (AM) fungal symbionts on host roots over multiple generations. We find that when spatial structure is reduced, by mixing soil, the relative success of the more cooperative AM fungal species increases. This challenges previous suggestions that high spatial structuring is critical for stabilizing cooperation in the mycorrhizal mutualism. More generally our results show, both theoretically and empirically, that contrary to expectations spatial structuring can select against cooperation. datafileAmNatqpCR, plant biomass, nutrient content and colonization data

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    DANS-EASY
    Dataset . 2012
    Data sources: B2FIND
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    DRYAD; ZENODO; NARCIS
    Dataset . 2012
    License: CC 0
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    Authors: Waelbroeck, Claire; Lougheed, Bryan C; Vázquez Riveiros, Natalia; Missiaen, Lise; +59 Authors

    Undatable run on 2019-01-09 15:38:47. nsim=10000 bootpc=10 xfactor=0.1 combine=Yes

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    PANGAEA
    Dataset . 2019
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2019
      Data sources: B2FIND
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Liebrand, Diederik; Raffi, Isabella; Fraguas, Ángela; Laxenaire, Rémi; +11 Authors

    Pelagic sediments from the subtropical South Atlantic Ocean contain geographically extensive Oligocene ooze and chalk layers that consist almost entirely of the calcareous nannofossil Braarudosphaera. Poor recovery and the lack of precise dating of these horizons in previous studies has limited our understanding of the exact number of acmes, their timing and durations, and the causes of their recurrence. Here we present a high-resolution, astronomically tuned stratigraphy of Braarudosphaera oozes (29.5-27.9 Ma) from Ocean Drilling Program Site 1264 in the subtropical southeastern Atlantic Ocean. We identify seven acme events in the Braarudosphaera abundance record. The longest lasting acme event corresponds to a strong minimum in the ~2.4-My eccentricity cycle, and four acme events coincide with ~110-ky and 405-ky eccentricity maxima. We propose that eccentricity-modulated precession forcing of the freshwater budget of the South Atlantic Ocean resulted in the episodic formation of a shallow pycnocline and hyperstratification of the upper water column. We speculate that stratified surface water conditions may have served as a virtual sea floor, which facilitated the widespread Braarudosphaera acmes. This explanation reconciles the contrasting distribution patterns of Braarudosphaera in the modern ocean, limited largely to shallow water coastal settings, compared to their relatively brief and expanded oceanic distribution in the past. Supplement to: Liebrand, Diederik; Raffi, Isabella; Fraguas, Ángela; Laxenaire, Rémi; Bosmans, Joyce H C; Hilgen, Frederik J; Wilson, Paul A; Batenburg, Sietske J; Beddow, Helen M; Bohaty, Steven M; Bown, Paul R; Crocker, Anya J; Huck, Claire E; Lourens, Lucas Joost; Sabia, Luciana (2018): Orbitally Forced Hyperstratification of the Oligocene South Atlantic Ocean. Paleoceanography and Paleoclimatology, 33(5), 511-529

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    PANGAEA
    Dataset . 2018
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2018
      Data sources: B2FIND
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    Authors: Tzedakis, Polychronis C; Margari, Vasiliki; Skinner, Luke C; Menviel, Laurie; +7 Authors

    XRF Analysis: Archive halves of sections from Core MD01-2444 were analysed using an Avaatech XRF core scanner at the University of Cambridge. The core surface was carefully scraped cleaned and covered with a 4-mm thin SPEXCertiPrep Ultralene foil to avoid contamination and minimize desiccation. Each section was measured using a current of 0.2mA at three different voltages: 10 kV, 30 kV using a thin lead filter, and 50 kV using a copper filter. XRF data were collected every 2.5 mm. The length and width of the irradiated surface was 2.5 and 12 mm, respectively, with a count time of 40s. The record was generated by D.A. Hodell and S. Crowhurst. Age model: The age model was developed by aligning the abrupt transitions of d18O record of G. bulloides in core MD01-2444 to warming and cooling events in the NGRIP d18Oice record, presented on: (i) the GICC05 timescale [Svensson, A. et al. A 60,000 year Greenland stratigraphic ice core chronology. Clim. Past 4, 47–57 (2008)]; and (ii) the WD2014: modified timescale, whereby NGRIP GICC05 ice ages 31.2–67.2 ka are multiplied by 1.0063. [Buizert, C. et al. The WAIS Divide deep ice core WD2014 chronology – Part 1: Methane synchronization (68–31 ka BP) and the gas age–ice age difference. Clim. Past 11, 153-173 (2015)].

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    PANGAEA
    Dataset . 2020
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2020
      Data sources: B2FIND
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    Authors: Senden, Mario; Reuter, Niels; van den Heuvel, Martijn P.; Goebel, Rainer; +2 Authors

    Higher cognition may require the globally coordinated integration of specialized brain regions into functional networks. A collection of structural cortical hubs—referred to as the rich club—has been hypothesized to support task-specific functional integration. In the present paper, we use a whole-cortex model to estimate directed interactions between 68 cortical regions from functional magnetic resonance imaging activity for four different tasks (reflecting different cognitive domains) and resting state. We analyze the state-dependent input and output effective connectivity (EC) of the structural rich club and relate these to whole-cortex dynamics and network reconfigurations. We find that the cortical rich club exhibits an increase in outgoing EC during task performance as compared with rest while incoming connectivity remains constant. Increased outgoing connectivity targets a sparse set of peripheral regions with specific regions strongly overlapping between tasks. At the same time, community detection analyses reveal massive reorganizations of interactions among peripheral regions, including those serving as target of increased rich club output. This suggests that while peripheral regions may play a role in several tasks, their concrete interplay might nonetheless be task-specific. Furthermore, we observe that whole-cortex dynamics are faster during task as compared with rest. The decoupling effects usually accompanying faster dynamics appear to be counteracted by the increased rich club outgoing EC. Together our findings speak to a gating mechanism of the rich club that supports fast-paced information exchange among relevant peripheral regions in a task-specific and goal-directed fashion, while constantly listening to the whole network.,DATA_TASK_3DMOV_HP_CSF_WDBriefly, data comes from five functional runs consisting of a resting-state measurement (eyes closed), four individual task measurements including a visual n-back (n=2) task (Kirchner, 1958), the Eriksen flanker task (Eriksen & Eriksen, 1974), a mental rotation task (Shepard & Metzler, 1971), and a verbal odd-man-out task (Flowers & Robertson, 1985). All runs comprise 192 data points with tasks being continuously performed during this period. For the n-back and flanker task, stimuli were presented at a rate of 0.5 Hz; for the mental rotation and odd-man out tasks they were presented at a rate of 0.25 Hz. Task sequence was counterbalanced across participants with the exception that the resting state functional run was always acquired first to prevent carry-over effects (Grigg & Grady, 2010). The data were acquired using a 3 Tesla Siemens Prisma Fit (upgraded Tim Trio) scanner and a 64-channel head coil. Initial preprocessing was performed using BrainVoyager QX (v2.6; Brain Innovation, Maastricht, the Netherlands). This includes slice scan time correction, 3D-motion correction, high-pass filtering with a frequency cutoff of .01 Hz, and registration of functional and anatomical images. Subsequently, using MATLAB (2013a, The MathWorks,Natick, MA), signals were cleaned by performing wavelet despiking (Patel & Bullmore, 2015) and regressing out a global noise signal given by the first principal component of signals observed within the cerebrospinal fluid of the ventricles. Next, voxels were uniquely assigned to one of the 68 cortical ROIs specified by the DK atlas and an average BOLD time-series was computed for each region as the mean time-series over all voxels of that region., CC0 1.0

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    DANS-EASY
    Dataset . 2017
    Data sources: B2FIND
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    DRYAD; ZENODO; NARCIS
    Dataset . 2018
    License: CC 0
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      DANS-EASY
      Dataset . 2017
      Data sources: B2FIND
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      DRYAD; ZENODO; NARCIS
      Dataset . 2018
      License: CC 0
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    Authors: Schreuder, Laura T; Stuut, Jan-Berend W; Korte, Laura F; Sinninghe Damsté, Jaap S; +1 Authors

    Long chain n-alkanes are terrestrial higher plant biomarkers used to reconstruct continental paleoclimatic and paleohydrological conditions with marine sedimentary archives. Latitudinal variation in their concentration and distribution in marine sediments relatively close to the continent has been widely studied, but little is known on how far this continental signal extends into the ocean. Furthermore, no studies have examined the seasonal variation in the deposition of these biomarkers in marine sediments. Here we studied longitudinal variation in the composition of long chain n-alkanes and two other terrestrial higher plant biomarkers (long chain n-alkanols and long chain fatty acids) in atmospheric particles, as well as longitudinal and seasonal variation in long chain n-alkanes in sinking particles in the ocean at different water depths and in surface sediments, all collected along a 12°N transect across the tropical North Atlantic Ocean. The highest abundance of all three biomarker classes was closest to the African coast, as expected, because they are transported with Saharan dust and the largest part of the dust is deposited close to the source. At this proximal location, the seasonal variability in long chain n-alkane flux and the chain length distribution of the n-alkanes in sinking particles was most pronounced, due to seasonal change in the dust source or due to change in vegetation composition in the source area, related to the position of the Intertropical Convergence Zone (ITCZ). In contrast, in the open ocean the seasonal variability in both the long chain n-alkane flux and chain length distribution of the n-alkanes was low. The abundance of the alkanes was also lower, as expected because of the larger source-to-sink distance. At the western part of the transect, close to South America, we found an additional source of the alkanes in the sinking particles during spring and autumn in the year 2013. The d13C of the alkanes in the surface sediment closest to the South American continent indicated that the isotope signal is likely derived from C3 vegetation from the Amazon, implying an input from the Amazon River, as there is no significant aeolian input from South America there since the prevailing wind direction is from the east. Finally, the concentration of the alkanes was similar in the material collected from the atmosphere, the particles collected while settling through the marine water column, and in the surface sediments, providing evidence that degradation of long chain n-alkanes from the atmosphere to settling at the sediment-water interface at deep open ocean sites is minimal. Supplement to: Schreuder, Laura T; Stuut, Jan-Berend W; Korte, Laura F; Sinninghe Damsté, Jaap S; Schouten, Stefan (2018): Aeolian transport and deposition of plant wax n -alkanes across the tropical North Atlantic Ocean. Organic Geochemistry, 115, 113-123

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    PANGAEA
    Dataset . 2017
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2017
      Data sources: B2FIND
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Hoogakker, Babette A A; Chapman, Mark R; McCave, I Nick; Hillaire-Marcel, Claude; +3 Authors

    High resolution flow speed reconstructions of two core sites located on Gardar Drift in the northeast Atlantic Basin and Orphan Knoll in the northwest Atlantic Basin reveal a long-term decrease in flow speed of Northeast Atlantic Deep Water (NEADW) after 6,500 years. Benthic foraminiferal oxygen isotopes of sites currently bathed in NEADW show a 0.2per mil depletion after 6,500 years, shortly after the start of the development of a carbon isotope gradient between NEADW and Norwegian Sea Deep Water. We consider these changes in near-bottom flow vigor and benthic foraminiferal isotope records to mark a significant reorganization of the Holocene deep ocean circulation, and attribute the changes to a weakening of NEADW flow during the mid to late Holocene that allowed the shoaling of Lower Deep Water and deeper eastward advection of Labrador Sea Water into the northeast Atlantic Basin. MD99-2251 originally published in Ellsion et al., (2006). Conversion to calendar years before present (cal. yrs BP) with CALIB 501 (Stuiver et al., 1993) using marine04 as calibration data set. Mean ages are the arithmetic means of the age ranges given by the program. Supplement to: Hoogakker, Babette A A; Chapman, Mark R; McCave, I Nick; Hillaire-Marcel, Claude; Ellison, Christopher RW; Hall, Ian R; Telford, Richard J (2011): Dynamics of North Atlantic Deep Water masses during the Holocene. Paleoceanography, 26(4), PA4214

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    PANGAEA
    Dataset . 2011
    Data sources: B2FIND
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    PANGAEA - Data Publisher for Earth and Environmental Science
    Other dataset type . 2011
    License: CC BY
    Data sources: Datacite
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      PANGAEA
      Dataset . 2011
      Data sources: B2FIND
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      PANGAEA - Data Publisher for Earth and Environmental Science
      Other dataset type . 2011
      License: CC BY
      Data sources: Datacite
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    Authors: Mendoza, Irene; Peres, Carlos Augusto; Morellato, Leonor Patricia C;

    Changes in the life cycle of organisms (i.e. phenology) are one of the most widely used early-warning indicators of climate change, yet this remains poorly understood throughout the tropics. We exhaustively reviewed any published and unpublished study on fruiting phenology carried out at the community level in the American tropics and subtropics (latitudinal range: 26°N?26°S) to (1) provide a comprehensive overview of the current status of fruiting phenology research throughout the Neotropics; (2) unravel the climatic factors that have been widely reported as drivers of fruiting phenology; and (3) provide a preliminary assessment of the potential phenological responses of plants under future climatic scenarios. Despite the large number of phenological datasets uncovered (218), our review shows that their geographic distribution is very uneven and insufficient for the large surface of the Neotropics (~ 1 dataset per ~ 78,000 km2). Phenological research is concentrated in few areas with many studies (state of São Paulo, Brazil, and Costa Rica), whereas vast regions elsewhere are entirely unstudied. Sampling effort in fruiting phenology studies was generally low: the majority of datasets targeted fewer than 100 plant species (71%), lasted 2 years or less (72%), and only 10.4% monitored > 15 individuals per species. We uncovered only 10 sites with ten or more years of phenological monitoring. The ratio of numbers of species sampled to overall estimates of plant species richness was wholly insufficient for highly diverse vegetation types such as tropical rainforests, seasonal forest and cerrado, and only slightly more robust for less diverse vegetation types, such as deserts, arid shrublands and open grassy savannas. Most plausible drivers of phenology extracted from these datasets were environmental (78.5%), whereas biotic drivers were rare (6%). Among climatic factors, rainfall was explicitly included in 73.4% of cases, followed by air temperature (19.3%). Other environmental cues such as water level (6%), solar radiation or photoperiod (3.2%), and ENSO events (1.4%) were rarely addressed. In addition, drivers were analyzed statistically in only 38% of datasets and techniques were basically correlative, with only 4.8% of studies including any consideration of the inherently autocorrelated character of phenological time series. Fruiting peaks were significantly more often reported during the rainy season both in rainforests and cerrado woodlands, which is at odds with the relatively aseasonal character of the former vegetation type. Given that climatic models predict harsh future conditions for the tropics, we urgently need to determine the magnitude of changes in plant reproductive phenology and distinguish those from cyclical oscillations. Long-term monitoring and herbarium data are therefore key for detecting these trends. Our review shows that the unevenness in geographic distribution of studies, and diversity of sampling methods, vegetation types, and research motivation hinder the emergence of clear general phenological patterns and drivers for the Neotropics. We therefore call for prioritizing research in unexplored areas, and improving the quantitative component and statistical design of reproductive phenology studies to enhance our predictions of climate change impacts on tropical plants and animals. This file contains collated datasets including phenological information of fruiting in the Neotropics. They are part of an invited review submitted to Global and Planetary Change. Each dataset collated in our review was distinguished with a different ID. Complete reference, geographical coordinates (latitude and longitude), information about sampling procedures, sampling effort in terms of the number of individuals, species or seed traps used, study length monitoring, vegetation type and life herb forms are included. Supplement to: Mendoza, Irene; Peres, Carlos Augusto; Morellato, Leonor Patricia C (2016): Continental-scale patterns and climatic drivers of fruiting phenology: A quantitative Neotropical review. Global and Planetary Change

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    PANGAEA
    Dataset . 2016
    Data sources: B2FIND
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    PANGAEA - Data Publisher for Earth and Environmental Science
    Other dataset type . 2016
    License: CC BY
    Data sources: Datacite
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      PANGAEA
      Dataset . 2016
      Data sources: B2FIND
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      PANGAEA - Data Publisher for Earth and Environmental Science
      Other dataset type . 2016
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Tzedakis, Polychronis C; Margari, Vasiliki; Skinner, Luke C; Menviel, Laurie; +7 Authors

    Benthic foraminifera oxygen isotopes: The benthic isotope record was generated by the late N.J. Shackleton. Measurements were carried out in the Godwin Laboratory for Palaeoclimate Research (University of Cambridge), using a VG PRISM mass spectrometer. Where possible two or three separate analyses of different benthic species were made in each sample; a correction factor was applied according to the species and the average of all the corrected values at each level is shown in the figures. The following species were analysed, and adjusted as indicated: Cibicidoides sp.: +0.51; Uvigerina peregrina and similar specimens: 0.0; Globobulimina affinis: -0.4; Cibicidoides wuellerstorfi, +0.64; Globocassidulina sp.: -0.1; Hoeglundina elegans: -0.7. These adjustments are optimized for this particular core in accordance with the long-standing convention by which Uvigerina peregrina is assumed to deposit oxygen in isotopic equilibrium. Results are reported with reference to the international standard VPDB and the precision is better than ±0.08‰ for d18O. Age model: The age model was developed by aligning the abrupt transitions of d18O record of G. bulloides in core MD01-2444 to warming and cooling events in the NGRIP d18Oice record, presented on: (i) the GICC05 timescale [Svensson, A. et al. A 60,000 year Greenland stratigraphic ice core chronology. Clim. Past 4, 47–57 (2008)]; and (ii) the WD2014: modified timescale, whereby NGRIP GICC05 ice ages 31.2–67.2 ka are multiplied by 1.0063. [Buizert, C. et al. The WAIS Divide deep ice core WD2014 chronology – Part 1: Methane synchronization (68–31 ka BP) and the gas age–ice age difference. Clim. Past 11, 153-173 (2015)].

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    PANGAEA
    Dataset . 2020
    Data sources: B2FIND
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